Modeling and assessing the effects of land use changes on runoff generation with the CLUE-s and WetSpa models

Theoretical and Applied Climatology - Land use change is an important determinant of hydrological processes and is known to affect hydrological parameters such as runoff volume, flood frequency,...     

Forecasting monthly inflow with extreme seasonal variation using the hybrid SARIMA-ANN model

The optimal operation of dam reservoirs can be programmed and managed by predicting the inflow to these structures more accurately. To this end, there are various linear and nonlinear models. However, some hydrological problems like inflow with extreme seasonal variation are not purely linear or nonlinear. To improve the forecasting accuracy of this phenomenon, a linear Seasonal Auto Regressive Integrated Moving Average (SARIMA) model is combined with a nonlinear Artificial Neural Network (ANN) model. This new model is used to predict the monthly inflow to the Jamishan dam reservoir in West Iran. A comparison of the SARIMA and ANN models with the proposed hybrid model’s results is provided accordingly. More specifically, the models’ performance in forecasting base and flood flows is evaluated. The effect of changing the forecasting period length on the models’ accuracy is studied. The results of increasing the number of SARIMA model parameters up to five are investigated to achieve more accurate forecasting. The hybrid model predicts peak flood flows much better than the individual models, but SARIMA outperforms the other models in predicting base flow. The obtained results indicate that the hybrid model reduces the overall forecast error more than the ANN and SARIMA models. The coefficient of determination of the hybrid, ANN and SARIMA models were 0.72, 0.64 and 0.58, and the root mean squared error values were 1.02, 1.16 and 1.27 respectively, during the forecast period. Changing the forecasting length also indicated that these models can be used in the long term without increasing the forecast error.     

Artificial recharge efficiency assessment by soil water balance and modelling approaches in a multi-layered vadose zone in a dry region

To assess recharge through floodwater spreading, three wells, approx. 30 m deep, were dug in a 35-year-old basin in southern Iran. Hydraulic parameters of the layers were measured. One well was equipped with pre-calibrated time domain reflectometry (TDR) sensors. The soil moisture was measured continuously before and after events. Rainfall, ponding depth and the duration of the flooding events were also measured. Recharge was assessed by the soil water balance method, and by calibrated (inverse solution) HYDRUS-1D. The results show that the 15 wetting front was interrupted at a layer with fine soil accumulation over a coarse layer at the depth of approx. 4 m. This seemed to occur due to fingering flow. Estimation of recharge by the soil water balance and modelling approaches showed a downward water flux of 55 and 57% of impounded floodwater, respectively.     

Comparing grain size distribution of sediment and original soil under raindrop detachment and raindrop-induced and flow transport mechanism

The grain size distribution (GSD) of sediment in comparison with the original soil GSD is discussed under different slopes (5, 15 and 25%) and rainfall intensities (30, 60 and 90 mm h^–1 with respective duration of 30, 15 and 10 min) but identical runoff (15 mm). The sediment quantification was carried out by raindrop-induced flow transport (RIFT) or/and transport by flow (FT) using a rainfall simulator and a 6 × 1 m² erosion plot and a silt loam. The results show a high degree of enrichment for size classes of 2–4 and 4–8 μm and a high degree of depletion for size classes of >63 μm under different slopes and rainfall intensities. In addition, the results show that the experimental enrichment ratio (ER) for particle size <16 μm under different slopes and rainfall intensities was greater than 1, while the ER for particle size >32 μm was less than 1.     

Factors associated with unnecessary requests for an ambulance by non-traumatic patients after the acute earthquake responding phase: a qualitative content analysis

The pre-hospital emergency staff played a key role in transferring the injured patients to health centers. Usually, they reported changes in their decisions on the transfer of non-traumatic patients to hospitals. So, this study was aimed to explore the reasons for unnecessarily requesting an ambulance by non-traumatic patients after the acute responding-to-earthquake phase. This study was a qualitative study that data were analyzed by content analysis approach. Participants were eleven pre-hospital emergency technicians. Data were collected by three sessions of focus group discussion. Data analysis was led to emergence of a main theme: “feeling urgency due to turmoil and uncertainty.” This theme illustrates the basic approach of the inhabitants of the earthquake-stricken region when unnecessarily requesting an ambulance. This theme was derived from two main categories of “turbulent and uncertain conditions” and “psychological turmoil.” The category of “turbulent and uncertain conditions” was comprised of three subcategories: “unreliable care,” “inadequate facilities” and “turbulent living conditions.” The category of “psychological turmoil” was comprised of three subcategories: “psychological turmoil in survivors,” “healthcare providers deciding under pressure” and “turmoil in providing psychological and psychiatric services.” Ambulance dispatch may be unnecessarily performed owing to turbulent and unsure conditions and psychological turmoil in earthquake-stricken people and pre-hospital emergency staff. Providing earthquake-stricken people with psycho-medical services in their place of residence can significantly reduce the workload of pre-hospital emergency staff and consequently that of hospital staff and therefore save time and treatment costs and increase the quality of health services provided for the injured.

     

A nine-step approach for developing and implementing an “agricultural drought risk management plan”; case study: Alamut River basin in Qazvin,Iran

Occurrence of drought, as an inevitable natural climate feature, cannot be ceased while happening. However, costs of the consequences could be alleviated using mature scientific integrated approaches. To reduce the amount of damage, it is required to provide “Contingency” and “Mitigation” action plans. For this reason, development of efficient operating instructions for various regions based on weather conditions and field studies is needed as well as having a sophisticated understanding of socioeconomic situations. This paper describes an approach to provide the first national agricultural drought risk management plan for a river basin in Iran country as a pilot. The study lasted for 3 years as a national technical research project for the “soil conservation and watershed management research institute.” To reach the objectives, besides holding workshops and specialized think-tank meetings, field researches were done. Based on the socioeconomic data sources in the basin and the results of meetings by participation of local managers and residents, the final plan was developed. Moreover, in order to carry out this research, different climatic, agricultural and local information were collected in the watershed. In the next steps, potential risks and vulnerabilities of various agricultural sectors due to the hazard were evaluated. In this study, a nine-step approach to develop an agricultural drought risk management plan proposing different scientific–managerial phases based on the latest experts’ opinions, released international scientific best practices, and existing conditions governing the region was followed. With respect to the average income of US$ one million from agriculture and animal husbandry in the river basin, total drought loss varies from US$ 86,000 to US$ 258,000 for a range of light to very intense drought conditions, respectively. The setup of these nine executive phases defined monitoring, forecasting, and warning steps in working teams and managed the subprograms in partnership with stakeholders and decision-makers to mitigate the rate of drought damage from 30 to 47% (depending on the severity of the drought condition).

     

An Introduction to MODISI and SCMOD Methods for Correction of the MODIS Snow Assessment Algorithm

Detection, monitoring and precise assessment of the snow covered regions is an important issue. Snow cover area and consequently the amount of runoff generated from snowmelt have a significant effect on water supply management. To precisely detect and monitor the snow covered area we need satellite images with suitable spatial and temporal resolutions where we usually lose one for the other. In this study, products of two sensors MODIS and ASTER both on board of TERRA platform having low and high spatial resolution respectively were used. The objective of the study was to modify the snow products of MODIS by using simultaneous images of ASTER. For this, MODIS snow index image with high temporal resolution were compared with that of ASTER, using regression and correlation analysis. To improve NDSI index two methods were developed. The first method generated from direct comparison of ASTER averaged NDSI with those of MODIS (MODISI). The second method generated by dividing MODIS NDSI index into 10 codes according to their percentage of surface cover and then compared the results with the difference between ASTER averaged and MODIS snow indices (SCMOD). Both methods were tested against some 16 MODIS pixels. It is found that the precision of the MODISI method was more than 96%. This for SCMOD was about 98%. The RMSE of both methods were as good as 0.02.     

Location of Areas Prone to Flood Spreading Using GIS (Ilam Province,Iran)

Water Resources - The present study aimed to locate the areas prone to flood spreading in order to manage surface water resources. Therefore, the information layers of slope, land capability,...     

Seismic reliability assessment and the nonergodicity in the modelling parameter uncertainties

Modelling uncertainty can significantly affect the structural seismic reliability assessment. However, the limit state excursion due to this type of uncertainty may not be described by a Poisson process as it lacks renewal properties with the occurrence of each earthquake event. Furthermore, considering uncertainties related to ground motion representation by employing recorded ground motions together with modelling uncertainties is not a trivial task. Robust fragility assessment, proposed previously by the authors, employs the structural response to recorded ground motion as data in order to update prescribed seismic fragility models. Robust fragility can be extremely efficient for considering also the structural modelling uncertainties by creating a dataset of one-to-one assignments of structural model realizations and as-recorded ground motions. This can reduce the computational effort by more than 1 order of magnitude. However, it should be kept in mind that the fragility concept itself is based on the underlying assumption of Poisson-type renewal. Using the concept of updated robust reliability, considering both the uncertainty in ground motion representation based on as-recorded ground motion and non ergodic modelling uncertainties, the error introduced through structural reliability assessment by using the robust fragility is quantified. It is shown through specific application to an existing RC frame that this error is quite small when the product of the time interval and the standard deviation of failure rate is small and is on the conservative side.     

Assessment of geomorphological bank evolution of the alluvial threshold rivers based on entropy concept parameters

The complex stream bank profiles in alluvial channels and rivers that are formed after reaching equilibrium has been a popular topic of research for many geomorphologists and river engineers. The entropy theory has recently been successfully applied to this problem. However, the existing methods restrict the further application of the entropy parameter to determine the cross-section slope of the river banks. To solve this limitation, we introduce a novel approach in the extraction of the equation based on the calculation of the entropy parameter (λ) and the transverse slope of the bank profile at threshold channel conditions. The effects of different hydraulic and geometric parameters are evaluated on a variation of the entropy parameter. Sensitivity analysis on the parameters affecting the entropy parameter shows that the most effective parameter on the λ-slope multiplier is the maximum slope of the bank profile and the dimensionless lateral distance of the river banks.